Data Visualization for Beginners with Python & Power BI

This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. Mastering data visualization is a crucial skill in today’s data-driven world, and this course will help you unlock that potential. By learning both Python and Power BI, you’ll gain the ability to create impactful visualizations using the most popular tools in data science. You'll work with libraries like Matplotlib, Seaborn, and Plotly, and discover how these libraries can be used to build everything from line charts to interactive scatter plots. Simultaneously, you will also learn Power BI fundamentals, including importing and transforming data, creating dynamic models, and building interactive reports. The course is divided into two primary sections: one focusing on Python’s data visualization libraries, and the other on Power BI. You’ll start by mastering the core Python libraries, Matplotlib and Seaborn, before progressing to Plotly for interactive charts. In parallel, you will dive into Power BI, exploring Power Query fundamentals and data modeling techniques, followed by a deep dive into data visualization and publishing reports. By engaging in both Python and Power BI, you'll build comprehensive skills in data analysis and visualization that complement each other. This course is perfect for beginners who want to explore data visualization. If you are looking to enhance your skills in data science, business intelligence, or data-driven decision-making, this is the course for you. While no prior experience in Python or Power BI is required, familiarity with basic data concepts will be beneficial. This course is designed to take you from foundational knowledge to advanced skills in data visualization. By the end of the course, you will be able to create interactive and static visualizations in Python and Power BI, perform advanced data transformations, design interactive reports, and analyze complex datasets to extract valuable insights.